| 11. |
- Pellinen, T, et al.
(author)
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ITGB1-dependent upregulation of Caveolin-1 switches TGFβ signalling from tumour-suppressive to oncogenic in prostate cancer
- 2018
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In: Scientific reports. - : Springer Science and Business Media LLC. - 2045-2322. ; 8:1, s. 2338-
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Journal article (peer-reviewed)abstract
- Caveolin-1 (CAV1) is over-expressed in prostate cancer (PCa) and is associated with adverse prognosis, but the molecular mechanisms linking CAV1 expression to disease progression are poorly understood. Extensive gene expression correlation analysis, quantitative multiplex imaging of clinical samples, and analysis of the CAV1-dependent transcriptome, supported that CAV1 re-programmes TGFβ signalling from tumour suppressive to oncogenic (i.e. induction of SLUG, PAI-1 and suppression of CDH1, DSP, CDKN1A). Supporting such a role, CAV1 knockdown led to growth arrest and inhibition of cell invasion in prostate cancer cell lines. Rationalized RNAi screening and high-content microscopy in search for CAV1 upstream regulators revealed integrin beta1 (ITGB1) and integrin associated proteins as CAV1 regulators. Our work suggests TGFβ signalling and beta1 integrins as potential therapeutic targets in PCa over-expressing CAV1, and contributes to better understand the paradoxical dual role of TGFβ in tumour biology.
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| 12. |
- Lu, Yingchang, et al.
(author)
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A Transcriptome-Wide Association Study Among 97,898 Women to Identify Candidate Susceptibility Genes for Epithelial Ovarian Cancer Risk.
- 2018
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In: Cancer Research. - 0008-5472 .- 1538-7445. ; 78:18, s. 5419-5430
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Journal article (peer-reviewed)abstract
- .AbstractLarge-scale genome-wide association studies (GWAS) have identified approximately 35 loci associated with epithelial ovarian cancer (EOC) risk. The majority of GWAS-identified disease susceptibility variants are located in noncoding regions, and causal genes underlying these associations remain largely unknown. Here, we performed a transcriptome-wide association study to search for novel genetic loci and plausible causal genes at known GWAS loci. We used RNA sequencing data (68 normal ovarian tissue samples from 68 individuals and 6,124 cross-tissue samples from 369 individuals) and high-density genotyping data from European descendants of the Genotype-Tissue Expression (GTEx V6) project to build ovarian and cross-tissue models of genetically regulated expression using elastic net methods. We evaluated 17,121 genes for their cis-predicted gene expression in relation to EOC risk using summary statistics data from GWAS of 97,898 women, including 29,396 EOC cases. With a Bonferroni-corrected significance level of P < 2.2 × 10−6, we identified 35 genes, including FZD4 at 11q14.2 (Z = 5.08, P = 3.83 × 10−7, the cross-tissue model; 1 Mb away from any GWAS-identified EOC risk variant), a potential novel locus for EOC risk. All other 34 significantly associated genes were located within 1 Mb of known GWAS-identified loci, including 23 genes at 6 loci not previously linked to EOC risk. Upon conditioning on nearby known EOC GWAS-identified variants, the associations for 31 genes disappeared and three genes remained (P < 1.47 × 10−3). These data identify one novel locus (FZD4) and 34 genes at 13 known EOC risk loci associated with EOC risk, providing new insights into EOC carcinogenesis.Significance: Transcriptomic analysis of a large cohort confirms earlier GWAS loci and reveals FZD4 as a novel locus associated with EOC risk. Cancer Res; 78(18); 5419–30. ©2018 AACR.
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| 20. |
- Pelttari, L. M., et al.
(author)
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Gene-panel testing of breast and ovarian cancer patients identifies a recurrent RAD51C duplication
- 2018
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In: Clinical Genetics. - : Wiley. - 0009-9163. ; 93:3, s. 595-602
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Journal article (peer-reviewed)abstract
- Gene-panel sequencing allows comprehensive analysis of multiple genes simultaneously and is now routinely used in clinical mutation testing of high-risk breast and ovarian cancer patients. However, only BRCA1 and BRCA2 are often analyzed also for large genomic changes. Here, we have analyzed 10 clinically relevant susceptibility genes in 95 breast or ovarian cancer patients with gene-panel sequencing including also copy number variants (CNV) analysis for genomic changes. We identified 12 different pathogenic BRCA1, BRCA2, TP53, PTEN, CHEK2, or RAD51C mutations in 18 of 95 patients (19%). BRCA1/2 mutations were observed in 8 patients (8.4%) and CHEK2 protein-truncating mutations in 7 patients (7.4%). In addition, we identified a novel duplication encompassing most of the RAD51C gene. We further genotyped the duplication in breast or ovarian cancer families (n=1149), in unselected breast (n=1729) and ovarian cancer cohorts (n=553), and in population controls (n=1273). Seven additional duplication carries were observed among cases but none among controls. The duplication associated with ovarian cancer risk (3/590 of all ovarian cancer patients, 0.5%, P=.032 compared with controls) and was found to represent a large fraction of all identified RAD51C mutations in the Finnish population. Our data emphasizes the importance of comprehensive mutation analysis including CNV detection in all the relevant genes.
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